Predicting native language from gaze

Yevgeni Berzak, Chie Nakamura, Suzanne Flynn, Boris Katz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A fundamental question in language learning concerns the role of a speaker's first language in second language acquisition. We present a novel methodology for studying this question: analysis of eye-movement patterns in second language reading of free-form text. Using this methodology, we demonstrate for the first time that the native language of English learners can be predicted from their gaze fixations when reading English. We provide analysis of classifier uncertainty and learned features, which indicates that differences in English reading are likely to be rooted in linguistic divergences across native languages. The presented framework complements production studies and offers new ground for advancing research on multilingualism.

Original languageEnglish
Title of host publicationACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)
Pages541-551
Number of pages11
ISBN (Electronic)9781945626753
DOIs
StatePublished - 2017
Externally publishedYes
Event55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, Canada
Duration: 30 Jul 20174 Aug 2017

Publication series

NameACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers)
Volume1

Conference

Conference55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
Country/TerritoryCanada
CityVancouver
Period30/07/174/08/17

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Artificial Intelligence
  • Software
  • Linguistics and Language

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